Representation of complex mammary parenchyma texture in tomosynthesis using simplex noise simulations

Bruno Barufaldi; Chloe J. Choi; Joao P. V. Teixeira; Magnus Dustler; Raphael B. Englander; Thaís G. do Rêgo; Yuri Malheiros; Telmo M. Silva Filho; Belayat Hossain; Juhun Lee; Andrew D. A. Maidment

doi:10.1117/12.3006839

1 April 2024 Representation of complex mammary parenchyma texture in tomosynthesis using simplex noise simulations

Bruno Barufaldi, Chloe J. Choi, Joao P. V. Teixeira, Magnus Dustler, Raphael B. Englander, Thaís G. do Rêgo, Yuri Malheiros, Telmo M. Silva Filho, Belayat Hossain, Juhun Lee, Andrew D. A. Maidment

Author Affiliations +

Proceedings Volume 12925, Medical Imaging 2024: Physics of Medical Imaging; 1292548 (2024) https://doi.org/10.1117/12.3006839
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

The mammary parenchyma is a complex arrangement of tissues that can greatly vary among individuals, potentially masking cancers in breast screening images. In this work, we propose a Simplex-based method to simulate anatomical patterns and textures seen in digital breast tomosynthesis. Our approach involves selecting appropriate Simplex noise parameters to represent distinct categories of breast parenchyma with variable volumetric breast density (%VBD). We use volumetric coarse masks (70 × 60 × 50 mm3) to outline patches of both dense and adipose tissues. These masks serve as a foundation for volumetric and multi-scale Simplex-based noise distributions. The Simplex-based noise distributions are normalized and thresholded using gradient level sets selected to binarize specific Simplex frequencies. The Simplex frequencies are summed and binarized using post-hoc thresholds, resulting in patches of tissue tailored to represent anatomic-like structures seen in digital breast tomosynthesis (DBT) images. We simulate DBT projections and reconstructions of the patches of breast tissue following the acquisition geometry and exposure settings of a clinical tomosynthesis system. We calculate the power spectra and estimate the power-law exponent (β) using a sample of DBT reconstructions (n=500, equally stratified by four density classes). Our findings reveal an absolute β value of 3.0, indicative of the improvements achieved in both the performance and realism of the breast tissue simulation. In summary, our proposed Simplex-based method enhances realism and texture variations, ensuring the presence of anatomical and quantum noise at levels consistent with the image quality expected in breast screening exams.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Bruno Barufaldi, Chloe J. Choi, Joao P. V. Teixeira, Magnus Dustler, Raphael B. Englander, Thaís G. do Rêgo, Yuri Malheiros, Telmo M. Silva Filho, Belayat Hossain, Juhun Lee, and Andrew D. A. Maidment "Representation of complex mammary parenchyma texture in tomosynthesis using simplex noise simulations", Proc. SPIE 12925, Medical Imaging 2024: Physics of Medical Imaging, 1292548 (1 April 2024); https://doi.org/10.1117/12.3006839

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